An increasing number of domains are providing us with detailed trace data on
human decisions in settings where we can evaluate the quality of these
decisions via an algorithm. Motivated by this development, an emerging line of
work has begun to consider whether we can characterize and predict the kinds of
decisions where people are likely to make errors.
To